Paper published in a book (Scientific congresses, symposiums and conference proceedings)
MORL/D: Multi-Objective Reinforcement Learning based on Decomposition
Felten, Florian; Talbi, El-Ghazali; Danoy, Grégoire
2022In International Conference in Optimization and Learning (OLA2022)
Peer reviewed
 

Files


Full Text
MORL_D_ext__abstract.pdf
Author postprint (300.53 kB)
Request a copy

All documents in ORBilu are protected by a user license.

Send to



Details



Disciplines :
Computer science
Author, co-author :
Felten, Florian  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
Talbi, El-Ghazali ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Danoy, Grégoire  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
External co-authors :
no
Language :
English
Title :
MORL/D: Multi-Objective Reinforcement Learning based on Decomposition
Publication date :
2022
Event name :
International Conference in Optimization and Learning (OLA2022)
Event date :
18-07-2022 to 20-07-2022
Audience :
International
Main work title :
International Conference in Optimization and Learning (OLA2022)
Peer reviewed :
Peer reviewed
FnR Project :
FNR14762457 - Automating The Design Of Autonomous Robot Swarms, 2020 (01/05/2021-30/04/2024) - Gregoire Danoy
Available on ORBilu :
since 14 June 2022

Statistics


Number of views
270 (80 by Unilu)
Number of downloads
9 (4 by Unilu)

WoS citations
 
1

Bibliography


Similar publications



Contact ORBilu